Why is image recognition a key function of AI?
Image recognition is an important application of AI techniques, as images usually act as sensory input for further problems to be solved.

For example, a self-driving car needs to take into account its environment; it needs to recognise the path/road it is driving on, obstacles, other traffic, traffic signs, etc. All this is visual input which needs to be recognised. Without image recognition a self-driving car would not be possible.

A machine that operates in a warehouse picking goods: in order to handle the goods, eg with a robotic arm, it needs to recognise where the goods are and what they look like, so that the arm can be controlled.

A system controlling a CCTV camera should be able to distinguish an intruder from an animal that happens to just walk past. Again, with image recognition and classification this could be achieved.

An AI system will react to sensory input from the 'outside' world, and act on it. The type of sensory input depends on the application: it could be a numerical value (like a bank balance), language (text or speech), tactile (eg a robotic hand), or visual.  If it is a stock brokering system, image recognition is not needed. Machine translation would also not need it. But for many real-world interactions, having 'eyes' is either necessary or at the very least useful.